非限定的概念获取表征重述方法

Nonrestrictive Concept-Acquisition by Representation Redescription

基于知识的问题求解需要一个丰富而相对完备的概念系统,尤其是当任务具有领域非限定特征时。本文以认知心理学领域的表征重述模型为理论基础,提出了一种基于对象表征的概念系统表征与发展方法,详细研究了概念在4种不同水平下的表征和发展过程。该研究突破了人工智能和认知心理学领域在这一问题研究上的局限性,有助于提高基于知识的系统的推理能力和问题求解能力。

A rich and complete concept system is required for Knowledge-based Problem Solving, especially when the problem is domain unrestrictive. This paper proposes an object-based representing method for concept system, focusing on the representation and development of concepts on four representing levels. Our approach overcomes the restriction on the research of concept system in both Artificial Intelligence and Cognitive Psychology and contributes to the improvement of reasoning and problem solving ability in knowledge-based systems.